The human visual system perceives surface colors consistently under a wide variety of scene illuminations. For example, to the human visual system, a white piece of paper remains resolutely white independent of the color of the illuminant (light source) under which the piece of paper is viewed. This phenomenon is known as “color constancy.”
In contrast, color imaging systems (e.g., digital cameras) are not naturally adaptive like the human visual system. Accordingly, a digital camera cannot acceptably reproduce a scene's actual colors without compensating for the influence of the color (color temperature) of the light source. For example, without accounting for the color of the light source, a picture taken under tungsten light will look yellowish, and a picture taken under florescent light will look bluish. Thus, the color of the light source must be determined so that the image data can be “corrected” to compensate for the effect of the light source. This process is commonly referred to as “color balancing” or “white balancing.”
In color/white balancing, the color of the scene illumination is either measured or estimated from the image data, and then the image data is adjusted to compensate. In some implementations, the camera is equipped with the functionality and processing capability needed to estimate the color of the light source from the image data. For example, a camera may be equipped with a light meter that can be used to identify the color of the light source. A camera may instead rely on a statistics-based computational approach in which all of the pixel color values in an image are averaged, and the image data is then adjusted so that the average of the pixel color values is gray. Alternatively, a photographer may calibrate the camera to a known reference color (e.g., a gray card) every time pictures are taken.
Conventional white balancing techniques can be problematic for a variety of reasons. For example, it may be impractical or too costly to equip each camera with a dedicated light meter. Use of a gray card may be impractical and inconvenient because the photographer has to carry and set up such a card and spend extra time taking a picture. Statistics-based techniques may be inaccurate in many scenarios because, for example, the average color of a scene may not actually be gray.